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/unsloth

Expert guidance for fast fine-tuning with Unsloth - 2-5x faster training, 50-80% less memory, LoRA/QLoRA optimization

From plugin
nanoresearch
1.3k16 skills9 commands

Claude Code

$ npx -y skills add OpenRaiser/NanoResearch --skill unsloth --agent claude-code

SKILL.md

unsloth.SKILL.md
name: unsloth
description: Expert guidance for fast fine-tuning with Unsloth - 2-5x faster training, 50-80% less memory, LoRA/QLoRA optimization
version: 1.0.0
author: Orchestra Research
license: MIT
tags: [Fine-Tuning, Unsloth, Fast Training, LoRA, QLoRA, Memory-Efficient, Optimization, Llama, Mistral, Gemma, Qwen]
dependencies: [unsloth, torch, transformers, trl, datasets, peft]

Unsloth Skill

Comprehensive assistance with unsloth development, generated from official documentation.

When to Use This Skill

This skill should be triggered when:

  • Working with unsloth
  • Asking about unsloth features or APIs
  • Implementing unsloth solutions
  • Debugging unsloth code
  • Learning unsloth best practices

Quick Reference

Common Patterns

*Quick reference patterns will be added as you use the skill.*

Reference Files

This skill includes comprehensive documentation in `references/`:

  • **llms-txt.md** - Llms-Txt documentation

Use `view` to read specific reference files when detailed information is needed.

Working with This Skill

For Beginners

Start with the getting_started or tutorials reference files for foundational concepts.

For Specific Features

Use the appropriate category reference file (api, guides, etc.) for detailed information.

For Code Examples

The quick reference section above contains common patterns extracted from the official docs.

Resources

references/

Organized documentation extracted from official sources. These files contain:

  • Detailed explanations
  • Code examples with language annotations
  • Links to original documentation
  • Table of contents for quick navigation

scripts/

Add helper scripts here for common automation tasks.

assets/

Add templates, boilerplate, or example projects here.

Notes

  • This skill was automatically generated from official documentation
  • Reference files preserve the structure and examples from source docs
  • Code examples include language detection for better syntax highlighting
  • Quick reference patterns are extracted from common usage examples in the docs

Updating

To refresh this skill with updated documentation: 1. Re-run the scraper with the same configuration 2. The skill will be rebuilt with the latest information

<!-- Trigger re-upload 1763621536 -->

Read more
@openraiser
Ships withnanoresearch

端到端自主 AI 科研引擎 — 从研究想法到完整论文,全程自动化 快速开始 · 效果展示 · 流水线 · Claude Code · 飞书机器人 🔬 NanoResearch 真正运行计算实验——它不仅生成代码,还能将代码提交到 GPU 集群执行训练,收集真实实验结果,生成论文配图,最终输出一篇有实验数据支撑的完整 LaTeX 论文。论文中的每一个数据、表格、图表都来自实际运行的实验结果,而非 LLM 编造。

Stars on GitHub

Momentum

stars in total
1.3k
Star history of OpenRaiser/NanoResearch on GitHub, a chart by star-history.com

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Questions about unsloth.

Which coding agents can use unsloth?
unsloth installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.